Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
383
datasets available to search
ShareScore release 0.9.0
Dataset results
383 results for “growth analysis”
Exploring the Exclusive Isolation of Pseudomonas syringae in Peltigera Lichens via metabolite analysis and growth assays - Appendix
<p>Lichen samples from Iceland were collected from the genera Peltigera, Cladonia, and Stereocaulon in March 2023 at Heidmork forest, Oskjuhlid hill, and the shores of Ellidaa in Arbaejarstifla. All specimens underwent morphological analysis, and corresponding vouchers have been deposited at the Icelandic Institute of Natural History.</p>
Data and code for: Nonlinear life table response analysis: Decomposing nonlinear and nonadditive population growth responses to changes in environmental drivers
<p>Life table response experiments (LTREs) decompose differences in population growth rate between environments into separate contributions from each underlying demographic rate. However, most LTRE analyses make the unrealistic assumption that the relationships between demographic rates and environmental drivers are linear and independent, which may result in diminished accuracy when these assumptions are violated. In this study, we compare the relative efficacy of linear and second-order LTRE analyses in capturing changes in population growth rate caused by environmental driver changes. To explore this question, we analyze demographic data collected for three long-lived plant species: <em>Ardisia escallonioides</em> (Pascarella & Horvitz, 1998), <em>Silene acaulis</em>, and <em>Bistorta vivipara</em> (Doak & Morris, 2010). This repository includes data files containing vital rate (survival, growth, reproduction) observations or models for our three case studies, as well as an R script in which we use these demographic data to calculate linear and second-order LTRE approximations of changes in population growth rate for each system and generate the figures we present in our paper.</p>
Growth and analysis of the tetragonal (ST12) germanium nanowires
<p>New semiconducting materials, such as state-of-the-art alloys, engineered composites and allotropes of well-established materials can demonstrate unique physical properties and generate wide possibilities for a vast range of applications. Here we demonstrate, for the first time, the fabrication of a metastable allotrope of Ge, tetragonal germanium (ST12-Ge), in nanowire form. Nanowires were grown in a solvothermal-like single-pot method using supercritical toluene as a solvent, at moderate temperatures (290–330 °C) and a pressure of ∼48 bar. One-dimensional (1D) nanostructures of ST12-Ge were achieved <em>via</em> a self-seeded vapour–liquid–solid (VLS)-like paradigm, with the aid of an <em>in situ</em> formed amorphous carbonaceous layer. The ST12 phase of Ge nanowires is governed by the formation of this carbonaceous structure on the surface of the nanowires and the creation of Ge–C bonds. The crystalline phase and structure of the ST12-Ge nanowires were confirmed by X-ray diffraction (XRD), high-resolution transmission electron microscopy (HRTEM) and Raman spectroscopy. The nanowires produced displayed a high aspect ratio, with a very narrow mean diameter of 9.0 ± 1.4 nm, and lengths beyond 4 μm. The ST12-Ge nanowire allotrope was found to have a profound effect on the intensity of the light emission and the directness of the bandgap, as confirmed by a temperature-dependent photoluminescence study.</p>
Can diet composition estimates using stable isotope analysis of feathers predict growth and condition in nestling mountain bluebirds (Sialia currucoides)
<p>Insectivorous birds breeding in seasonal environments provision their dependent young during periods when prey diversity and abundance vary. Consequently, the composition and nutritional value of diets parents feed to their offspring may differ within and among broods, potentially affecting the condition of nestlings. In a population of mountain bluebirds (<i>Sialia currucoides</i>), we used two methods to estimate diet composition for individual nestlings: direct observation of provisioning using video recordings at 5 and 9 days post-hatch, and stable isotopes of the δ<sup>13</sup>C and δ<sup>15</sup>N in nestling feathers and prey followed by analysis with mixing models. We determined the macronutrient content (% fat and lean mass) and estimated the metabolized energy from each type of prey. We evaluated whether different methods of estimating diet composition would produce similar results, and if the types of prey nestlings ate at one or both ages affected their morphology, growth rates, or blood ketone concentration. We found that bluebirds fed their young 5 main types of prey: beetles, cicadas, grasshoppers, insect larvae, and spiders. Both observational and mixing model estimates of diet composition indicated that larvae are traded-off with grasshoppers, and that fewer larvae are provided to nestlings as the season progresses. In evaluating how diet influences individual growth and condition, estimates from direct observations had greater explanatory power than those from mixing models, indicating that diets rich in the most energy-dense prey (greatest fat content; cicadas and larvae) were associated with larger size and higher body condition, and faster rate of mass gain and growth of tarsus. Lower value prey had more limited, specific effects on nestlings, but may still be important dietary components. While isotopic methods produced estimates of diet composition that were generally informative, when applied to explain the growth and condition of nestlings they proved less useful. </p>
Data from: Interannual radial growth response of Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco) to severe droughts: an analysis along a gradient of soil properties and rooting characteristics
<p>Dataset related to the publication: „Interannual radial growth response of Douglas-fir (<em>Pseudotsuga menziesii</em> (Mirb.) Franco) to severe droughts: an analysis along a gradient of soil properties and rooting characteristics”</p> <p>Information on the data and the tree species_site_key used can be found in the attached Read me file.</p>
Figure 7 in Effect of water stress on weed germination, growth characteristics, and seed production: a global meta-analysis
Figure 7. Results from the sensitivity analysis depicting variations in the overall effect size estimates (mean ± 95% confidence intervals [CIs]) of water-stress effects on (A) weed germination/emergence, (B) seedling radicle/root length, (C) plant height, and (D) leaf area when a particular study is omitted from the analysis. The vertical black solid and dashed lines represent overall effect sizes (mean ± 95% CIs) with all studies included.
Figure 3 in Effect of water stress on weed germination, growth characteristics, and seed production: a global meta-analysis
Figure 3. Overall water-stress effects on germination/emergence of grass and broadleaf weeds (top) and six weed families—Asteraceae, Fabaceae, Convolvulaceae, Amaranthaceae, Rubiaceae, and Poaceae (bottom). The vertical black dashed line represents zero effect. The black dots are overall mean effect sizes, and the black lines are 99% confidence intervals (CIs).The values in parentheses are the number of observations followed by the number of studies for each pair-wise comparison. The mean effect sizes were considered significantly different when their 99% CIs did not include zero.
Figure 4 in Effect of water stress on weed germination, growth characteristics, and seed production: a global meta-analysis
Figure 4. The log response ratio for germination and seedling radicle length of broadleaf (green dots/line) and grass (red dots/line) weed species as a function of water-stress intensity. Water stress increased as solution osmotic potential (ψsolution) decreased and vice versa.The subgroups for germination are 0 to −0.2, −0.2 to −0.4, −0.4 to −0.6, −0.6 to −0.8, −0.8 to −1.0, −1.0 to −1.4, and <−1.4 MPa, while the subgroups for radicle length are 0 to −0.2, −0.2 to −0.4, −0.4 to −0.6, −0.6 to −1.0, and <−1.0 MPa. Only ψsolution-based studies were used in this analysis. For each subgroup, the solid dots and lines represent mean effect sizes and their corresponding 99% confidence intervals (CIs).The mean effect sizes were considered significantly different when their 99% CIs did not include zero. Similarly, the water-stress effects were significantly different for each subgroup and among weed types only when their 99% CIs did not overlap with one another. The fitted lines represent a four-parameter logistic regression model, and the coefficients of the models are presented in Table 2.
Figure 1 in Effect of water stress on weed germination, growth characteristics, and seed production: a global meta-analysis
Figure 1. PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses; Page and McKenzie 2021) flow diagram highlighting the selection procedure of 86 scientific published papers included in the meta-analysis.
Figure 8 in Effect of water stress on weed germination, growth characteristics, and seed production: a global meta-analysis
Figure 8. Results from the sensitivity analysis depicting variations in the overall effect size estimates (mean ± 95% confidence intervals [CIs]) of water-stress effects on (A) branches/tillers per plant, (B) leaves per plant, (C) inflorescences per plant, (D) seeds per plant, (E) total biomass, (F) root biomass, (G) shoot biomass, and (H) root:shoot ratio, when a particular study is omitted from the analysis. The vertical black solid and dashed lines represent overall effect sizes (mean ± 95% CIs) with all studies included.
Figure 6 in Effect of water stress on weed germination, growth characteristics, and seed production: a global meta-analysis
Figure 6. Density plots depicting the distribution of the individual effect sizes for all 12 response variables considered in this meta-analysis: (A) weed seed germination/emergence; (B) radicle/root length, plant height, and leaf area; (C) branches/tillers per plant, leaves per plant, inflorescences per plant, and seeds per plant; and (D) total biomass, root biomass, shoot biomass, and root:shoot ratio.
Figure 2 in Effect of water stress on weed germination, growth characteristics, and seed production: a global meta-analysis
Figure 2. Overall water-stress effects on weed germination/emergence, growth characteristics, and seed production. The vertical black dashed line represents zero effect. The black dots are overall mean effect sizes, and the black lines are 95% confidence intervals (CIs). The values in parentheses are the number of observations followed by the number of studies for each pair-wise comparison. The mean effect sizes were considered significantly different when their 95% CIs did not include zero.
Figure 5 in Effect of water stress on weed germination, growth characteristics, and seed production: a global meta-analysis
Figure 5. The log response ratio for weed growth characteristics (plant height, leaf area, branches/tillers per plant, leaves per plant,root biomass, shoot biomass, and root:shoot ratio) and seed production (inflorescences per plant and seeds per plant) as a function of water-stress intensity. Water stress increased as soil moisture (% field capacity) decreased and vice versa. The green and red dots represent broadleaf and grass weed species, respectively. The solid black points and the lines represent mean effect sizes and their 99% confidence intervals (CIs) for low (>60%), moderate (30%–60%), and severe (<30% field capacity) water-stress subgroups. The mean effect sizes were considered significantly different when their 99% CIs did not include zero. Similarly, the water-stress effects were significantly different for each subgroup and among weed types only when their 99% CIs did not overlap with one another.
Data from: Live-cell analysis of IMPDH protein levels during yeast colony growth provides insights into the regulation of GTP synthesis
<p>Here we present real-time, live-cell analysis of accumulation of the Imd2 isoform of IMPDH in <em>Saccharomyces cervisiae</em> yeast cells forming a monolayer colony in a microfluidic device over a 50-hour time course. We observe two distinct phases of increased Imd2 accumulation: a guanine-insensitive phase early in outgrowth and a guanine-sensitive phase later, when cells become crowded. We show that the IMPDH inhibitor mycophenolic acid enhances both phases of increase. Deletion of a transcription attenuator upstream of the mRNA start site that decreases Imd2 mRNA synthesis in the presence of high GTP increases the baseline level of Imd2 protein ten-fold and abolishes guanine-sensitive but not guanine-insensitive induction. Our results suggest that at least two mechanisms of yeast Imd2 regulation exist, the known GTP-dependent attenuation of RNA polymerase II elongation and a GTP concentration-independent pathway that may be controlled by cell growth state.</p>
Fig 1 in Determination of limited histotrophy as the reproductive mode in Mustelus schmitti Springer, 1939 (Chondrichthyes: Triakidae): analysis of intrauterine growth of embryos
Fig 1. Mean embryo total length and standard deviation as a function of the ordinal day of the year considering the two consecutive years (2006 and 2007) for Mustelus schmitti embryos. Dashed line represents the linear model adjusted to the individual data, continuous line is for the Gompertz model and the pointed line represents the Von Bertalanffy growth curve.
Fig 3 in Determination of limited histotrophy as the reproductive mode in Mustelus schmitti Springer, 1939 (Chondrichthyes: Triakidae): analysis of intrauterine growth of embryos
Fig 3. Relationship between total dry weight (g) (Mustelus schmitti embryos and its yolk sac) and time (ordinal days), along 2006 and 2007. The bottom and top of the box are the first and third quartiles, and the band inside is the median, the ends of the whiskers represent the range of the distribution. This graphic shows a clear increase in mass that has been associated with matrotrophy.
Fig 2 in Determination of limited histotrophy as the reproductive mode in Mustelus schmitti Springer, 1939 (Chondrichthyes: Triakidae): analysis of intrauterine growth of embryos
Fig 2. Mean yolk mass and standard deviation as a function of the ordinal day of the year considering the two consecutive years (2006 and 2007) for Mustelus schmitti embryos. Using the same y axis values the continuous line represents the logistic curve adjusted for presence/absence of yolk sac, the probability of an embryo having external yolk sac is given by Yt=1/(1+e(-13.749 + 0.072*t)) for 2006 and Yt=1/(1+e(-10.472 + 0.054*t)) for 2007.
Micro-CT scans, whole-test meshes, and internal chamber segments of planktonic foraminifera for three-dimensional analysis of inter- and intra-specific variation in ontogenetic growth trajectories
<p> </p> <p>Here, we release tomographic reconstructions of 42 planktonic foraminifera from plankton tows and sediment traps, along with meshes and shrinkwrap meshes the whole tests and internal meshes of segmented chambers. Shrinkwrap meshes are test meshes that have been modified to close all pores and apertures in the test. Additionally, we have provided sample metadata for each specimen and volumetric measurements for the tests and chambers. This dataset was used in a study of ontogenetic growth in planktonic foraminifera and its variation within and among species.</p> <p> The CT-scans and reconstructions were obtained at Naturalis Biodiversity Center in Leiden, the Netherlands with a Zeiss Xradia 520 Versa micro-CT scanner. The meshes and segments were created at Yale University.</p> <ol> <li>Sample_Metadata.csv: Spreadsheet containing information on the sampling localities and dates for all specimens.</li> <li>Scan_data.csv: Spreadsheet containing metadata for all micro-CT scans including current strength, pixel size, voltage, image height, image width, and the number of images taken.</li> <li>Whole_Test_Measurements.csv: Spreadsheet containing measurements of linear dimensions (axis1, axis2, axis 3), total number of chambers, calcite test volume, calcite test surface area, shrinkwrap volumes, and and shrinkwrap surface areas for all specimens.</li> <li>Chamber_Measurements.csv: Spreadsheet containing measurements of individual internal chamber segments, including position from the final chamber (F-chamber), position from the first chamber (Chamber), volume, and surface area.</li> <li>CT_Scan_Stacks.zip: reconstructed micro-CT image stacks (.tif files) for each specimen.</li> <li>Meshes.zip: Meshes of the test calcite, the shrinkwrap, and the internal chamber segments for each specimen (.stl 3D mesh files). Regular test meshes are named with the format “SampleID.stl”, and shrinkwrap meshes are named “SampleID-WRAP.stl”. Chamber meshes are named “SampleID-CH#.stl” and “SampleID-CH#-Wrap.stl”. Chambers are numbered in relation to their position from the final chamber, with “CH1” being the final chamber and “CH2” being the penultimate chamber.</li> </ol> <p>This data is described and analyzed in the manuscript “Three-Dimensional Analysis of Inter- and Intraspecific Variation in Ontogenetic Growth Trajectories of Planktonic Foraminifera” submitted to the journal <em>Marine Micropaleontology.</em></p>
Figure. PCA analysis based on GH-MspI, GH-AluI, PRL, and DGAT1 loci in Turkish native cattle breeds (Turkish Grey - TG, East Anatolian Red - EAR, Anatolian Black - AB, and South Anatolian Red - SAR). in Growth hormone (GH), prolactin (PRL), and diacylglycerol acyltransferase (DGAT1) gene polymorphisms in Turkish native cattle breeds
Figure. PCA analysis based on GH-MspI, GH-AluI, PRL, and DGAT1 loci in Turkish native cattle breeds (Turkish Grey - TG, East Anatolian Red - EAR, Anatolian Black - AB, and South Anatolian Red - SAR).
Hepatic transcriptomic analysis reveals differential regulation of metabolic and immune pathways in three strains of chickens with distinct growth rate exposed to mixed parasites infections
<p><span>This dataset was generated from the study investigating hepatic gene expression in three strains of chickens: Ross-308 (R), Lohmann Brown Plus (LB), and Lohmann Dual (LD), 2 weeks after either an experimental infection (n = 18) with both <em>A. galli</em> and <em>H. gallinarum or kept as uninfected control (n = 12)</em>. </span></p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.